Genes Co-expression networks associated with the fatty acid profile of skeletal muscle and liver of pigs fed different levels and sources of oil

• Grant number: 22/10643-5
• Support Opportunities: Scholarships in Brazil - Doctorate
• Effective date (Start): January 01, 2023
• Effective date (End): February 28, 2026
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Aline Silva Mello Cesar
• Grantee: Simara Larissa Fanalli
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Associated research grant: 17/25180-2 - Effect of dietary oleic acid on fatty acid composition and inflammatory response profile in different tissues of pigs, AP.JP

Abstract

Pork is the most consumed meat in the world and a source of fatty acids in the human diet. Nutritional strategies have been used to promote alteration and improvement of the lipid profile of meat, increasing the beneficial effects on human health. The composition of fatty acids (FA) deposited in pig tissues can be modified through the diet adopted with different types of oils. However, the effects of dietary inclusion of oils such as canola, fish, and soybean on pig gene expression are mostly unknown. In this sense, our objective is to identify gene co-expression networks associated with the FA profile of skeletal muscle and liver of pigs fed different levels and sources of oil. In this study, data from 72 immunocastrated male pigs will be used, fed diets consisting of a basal diet of corn and soybean meal supplemented with 1.5% soybean oil (SOY1.5, a common level used in commercial pig production) or 3 % soybean oil (SOY3.0), or 3% canola oil (CO) or 3% fish oil (FO) for an experimental period of 98 days during the growing and finishing phases (18 animals/treatment). As well as the profile of FA deposited in skeletal muscle and liver. The association between the expressed genes and deposited FA will be estimated through the construction of co-expression networks from the RNA-Seq data (n = 72) with the normalized transcription counts per million (TPM), through the WGCNA package (Weighted Correlation Network Analysis) R and the functional enrichment and network analysis will be performed by the Cytoscape and DAVID software. The results expected here have a significant technological and innovation profile since they provide information relevant to systems biology knowledge and can point to targets to be explored in genomic selection.